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JAMES P. BIRK Arizona State University Tempe, AZ 85287-1604
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Computer-Assisted Learning IRexpert, an Infrared Interpretation Assistant D. Cabrol, J. P. Rabine, D. Ricard, and M. Rouillard LARTIC, Universite de Nice Sophia-Antipolis,F06108 Nice Cedex 2, France T. P. Forrest Dalhousie University, Halifax, NS, Canada B3H 4J3
Although microcomputers have been used for computerassisted learning for over a decade, they have not as yet come near to fulfilling the early expectations that many educators held for them. It is clear that still further experimentation needs to be carried out to explore ways in which the wtential of com~utersin the educational field may be mire effectively re'alized. From the types of soRware that have been accepted most widelv for use in other fields of endeavor, one obs&vation is clea;; these programs are all used as tools to assist the user in doing some task that is unrelated to the computer itself, but arises out of the user's own needs. A clear exception to this is found in the realm of computer games, whkre the user allows the computer to set the task. The wide acceptance of promams thatare used as tools to assist with some task (e.g.,bordprocessors, spreadsheets, database programs, CAD programs, etc.) suggests that this type of task-assisting program could also find wide acceptance for use in the field of chemical education. Indeed, several papers published recently in this Journul have described applications of general ~roductivitvtools: s~readsheets(1-18). .. database aoplicakons (19-i0), numerical equation solvers ( 2 1 - 2 j ~ symbolic eauation solvers (26) and statistical ~ackaees (27);and some others have presented tools that -are mire specifically designed for chemical applications, ranging in complexity from simple unit-conversion and chemical calculators (2830) to molecular modelling (3132) and computer-assisted synthesis programs (33). The type of task assistant we have attempted to create in this has been modelled after the-assistance that the instructors now teaching the subiect had themselves. when they learned to interpret infrared spectra in a prac: tical manner during their research work. When interpreting a spectrum, the range of resources normally available would have included: group-frequency charts and tables; books with verbal descriptions of patterns, peaks and regions; a library of spectra to use for comparison purposes; and also the help of fellow graduate students and the professor. Experience of this type, gained over a period of time, provides an experiential learning situation that results in effective development of skills in infrared spectral interpretation: it is. of course.. not practical to orovide everv student with such an experience. The descrided in this paper, IRexpert, provides the student with an interactive inhronme& inwhich these resources, in one form or another, are provided, thus allowing the student to gain valuable interpretation experience in a greatly compressed time frame.
120
Journal of Chemical Education
Resources Provided by IRexpert The resources provided are i n two forms: first, a database of factual information, including spectra-structure correlation data, descriptions of peaks and regions, and a library of full spectra of pure compounds; second, an expert system-analyst that will analyze the students spectrum, and attempt to assist with its interpretation. The concept of using- expert . systems in educational Dromams has led to enormous int&est, resulting in the appearance of books dedicated to the subject (3435): however, few applications in chemical education have been reported ( 3 6 45). There are several well-known expert systems for the analysis of infrared spectral data, such as PAIRS (461, CHEMICS (47), EXSPEC (481, CASE (491, and EXPERTISE (50). Some use several spectra simultaneously, such as SESAMI (51),a more recent version of the CASE system that uses C13 and 2D NMR as well as IR spectra. As well, there is an increasing interest in using artificial neural networks in chemistrv (52). and the techniaue has been shown to be effective i"n the classification of ihfrared spectra (53). However, while these systems may be very efficient at their goal of solving structural problems, they are not particularly well suited for ~edaeoeicuse. It must be remkmbered that, in the educationa~&ntext,the user is not a trained spectroscopist. The user is a beginner whose goal is not simply to solve the problem per se but to acquire knowledge that would help himiher to solve other problems. A neural network is particularly ineffective in explaining the reasons for its assignments; consequently, an expert system is more adaptable to accommodate this objective by providing some explanations, yet leaving scope for initiative and decision-making in order to promote significant participation by the student. The system is desiened to assist students with the intemretation of their spectra, but with the primary goal of assisting them in develooim their own expertise in understandine and interA
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Database Information This part of the program gives the student access to resources similar to those available in a library: books containing information about infrared spectral interpretation, and catalogues of spectra. The database can be accessed by selecting Information on the main menu of the program (Fig. 1). This menu provides access to information about the group frequency correlations, the regional disposition of structural groups, the typical spectral patterns of struc-
Your Spectrum Formula Solvent
a list of the potential groups, including the range, shape and intensity ofthe absorption. An example is shown in Figure 2. More details on any of the groups presented can be obtained bv calline uDon the next menu item, whicc offers ietailed information on the structural groups.
Possibilities Advice
Figure 1. The main menu of choices available to the student. tural groups, and to a spectral database for the display of complete spectra of compounds. The information is displayed on the screen without interfering with the display of the student's own spectrum, so that direct comparisons may be made. When the student selects the Informationoption, a second menu appears offering a choice of five types of information: 1. A Region;provides information on the types of p u p s and oeaks that are twicallv . found in the chasen reeion. - (The reeon is selected from a swond menu. 2. A Fr~guencyrwavenumber,, the student enters the panic-
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lnformation on Individual Structural Groups The program a t the moment uses 21 structural groups (see the table), most of which are divided into subcategories; for example, the ketone group is divided into five subgroups: aliphatic, conjugated, alpha halo, aromatic and alpha diketone. A request for information on a particular group places a plot of the characteristic peaks in the spectral window and gives a textual description in the window beneath the spectrum. (See Fig. 3.)
ular wavenumbcr and i s provided wlth a list of groups having absorption at that wavenumber. 3. A Group; if the student requests information on a struetural group, a graphical display of the expected peaks, as well as a textual description is provided. 4. Seueral g m q s ; a combination of groups chosen by the student is used to synthesize a spectral representation of the set of substructural units. 5. A Spectrum; a spectral library of typical wmpounds allows the student to see the spectrum as well as the structural famula of the compound.
The database information is presented to the student in different formats, depending upon the request. The facilities are described below, and examples of the response given to typical requests for d a t a b a e information are shown in Figures 2 to 5. lnformation on Spectral Regions
Figure 3. Screen showing response to a request for informationon a particular group.
Manv ex~eriencedchemists make a n initial evaluation of a s p k & m by a precursory scan of particular regions. In order to prompt the student to consider the different reprel&inary scanning of the spectrum, informagions in ; tion is provided on the various types of absorptions that might be expected in four separate regions: 40003100, 3100-2000,2000-1400, and 1400-700 em-'. When the student asks for information on a region helshe is provided with textual descriptions of the types of structural group that would be expected to be found in the particular regions. lnformation on Requested Frequencies Using this facility might be aptly compared to using a s occur at a articular fretable to look UD the m o u ~ that quency. lnsteai of a gbleiormat, however, the information is displayed in a text window in which the student may see
Figure 4. Screen showing a simulated spectrum of a combination of several groups.
Absorption possible at 1300 cm-' CARBOXYLIC ACID: C b stretchina. medium. medium between 1210 and 1330 ALCOHOL: OH bendlna. medium.. sharo. . . between 1290 and 1460 PRIMARYA ~ I N E : C-N stretching. medium, sharp, between 1000 and 1350. TERTIARY AMINE: G N stretching, medium, sharp, between 1290 and 1380. KETONE: >C=Obending, medium, sharp, between 1030 and 1330.
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Figure 2. Bottom portion of screen showing response to student's request for informationon a particular frequency.
Figure 5. Screen showing a library spectrum displayed under student's spectrum. Volume 70 Number 2
February 1993
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Principal Structural Groups
Carboxylic acid Alkyne Anhydride Tertiary arnine Tertiary amide Acid halide Ester
Alkene Aldehyde Primary arnine Primary amide Ketone Alkyl halide Ether
Alwhol Alkyl
Secondary amine Sewndary amide Nitro Aromatic ring Nitrile
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a. allyl ethyl ether
Simulation of Spectra from Groups
The fourth of the Information menu selections gives the student the opportunity to create a spectrum by combining several structural units. The simulated spectrum is shown in a separate window beneath the student's spectrum. (See Fig. 4.) Spectral Libraries
The last selection of the Information menu gives the student access to libraries of wmplete spectra of known compounds. (See Fig. 5.) The student chooses a library of spectra, and then selects a spectrum from a menu containing the names of the compounds in the library. The current collection consists of 320 spectra organized in libraries by functional group. There are currently 19 libraries, and the instructor may add new spectra or new libraries by using two programs CONVERT and SPECTRO. The CONVERT program takes spectra in JCAMP standard format and converts them to a format used by IRexpert. The program also allows the instructor to create a structure of the compound to display on the screen with the spectrum. The SPECTRO program is the library management program. Spectral Analysis by the Program
The second type of resource available in the program provides the student assistance with the analysis of hisher own soectrum. If a student wishes assistance with the interpretation of a specific spectrum, helshe must entera descriotion of that spectrum into the computer. The program proGdes a means bf entering spectral data (peak frequencies, intensities, and shapes), as well as composition and sample state data. The information is analyzed by the program so that it can suggest structural groups that might be present in the corn, pound. The entry of the spectral information requires that the student "read the spectrum and describe the absorpModify a peak tions by verbal indications of List the peaks the shape and intensity. The Add a blank zone menu choice Your spectrum, Remove a blankzone as the name implies, is the List the blank zone one that allows the student to File management enter information about the Change Scales spectrum that helshe wants to analyze. A samole menu disFigure 6. Spectral Editor play& the fulilayout of opMenu. tions is shown in Figure 6. The number of options presented in the menu depends upon the information already entered; for example, the options Modify peak and Remove peak are only shown aRer some peaks actually have been entered. The wavenumber of the individual peak may be indicated by moving the cursor across the spectral window, or by typing in the wavenumber; the terms used to describe the shape and intensity are selected from menu choices. 122
Journal of Chemical Education
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b. simulated spectrum FQXe 7. Sln~atedspectrum ot ally ethy ether created from the spectral editor (oelowjcompared wllh the rea spectrLrn (above). Figure 7 shows an example of a spectrum created by the program from such a description; the genuine spectrum of allyl ethyl ether also is shown for comparison with the one created from the data entry routine. A reasonable representation of the spectrum as "read" by the student can be created by the program. In using this spectral entry facility of the program, the student develops skills in reading and describing infrared spectrum, skills that are not developed while doing interpretation exercises from a textbook. Other information that may help in the interpretation of the spectrum also can be entered by the student. The Formula menu allows the student to enter information regarding the composition of the compound. The interpretation of infrared spectra often can be made easier if additional information is known about the compound. It is common practice to provide students with additional information, such as the molecular formula, or at least some partial information about the composition of the compound. The student can, therefore, include such information when it is available. This information is used by the program to limit the structural groups to those that fit within the constraints of the composition of the compound. The Solvent menu allows the student to indicate the sample state (film, disk, or solvent). It provides information about the solvents and draws a spectrum of the solvent (or mull medium) on the same screen as the student's spectrum (in a different color); example, Figure 8. This display shows clearly the regions of interference where masking of spectral peaks can occur. Averbal description of the solvent and its uses is given beneath the spectrum. Once the student h a entered a drscriptioo of the spectrum. an analvsis of the data can be rcaursted. The Possibilities men; provides access to a matching routine that comoares the data entered bv the student with the pro&am's database of spectral characteristics of functional erouos. and wnerates a list of suwestions of the structural Fragments &at could be present ;the compound. The stu-
Figure 8. Solvent superimposed when student indicates typed solvent used.
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There are seven groups suggested by your data They will be shown in sequence, starting with the better substantiated groups, ending with the less well identified groups. You may go down the list as far as you like, quitting at any time by pressing Esc Esc.
a rule-based expert system. It offers advice based on the information that the student has provided, and the information that the program has been able to derive from matching the student's data with the database information. In its advisorv capacitv the expert svstem may ask &her info&ationabout the-specthe student to trum and to make decisions on the presence or absence of particular structural groups. since this advice concerns the student's specific compound, the first function of the advisor is to check whether the student has entered adequate information for an analysis, and to prompt the student as to the t w e of information to enter. and where to look in the spectrum to find the absorbances due to particular groups. When the advisor determines that adequate information has been entered, it calls upon the peak matchine module to ~erforman analysis of the data. The potentiar groups arepresented to the student with pertinent comments and questions where appropriate. The advisor not only offers suggestions on the group being considered. but also mav ask the student to answer specific related to the group. As the last step in the consideration of a moup, the student is asked to make a decision about whethe;& not the group is present. After the potential groups have been considered, a summary is provided and compatibilities are checked among the groups and solvent.
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